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Diffstat (limited to 'src/cpu/operators/internal/CpuGemmAssemblyDispatch.h')
-rw-r--r-- | src/cpu/operators/internal/CpuGemmAssemblyDispatch.h | 198 |
1 files changed, 198 insertions, 0 deletions
diff --git a/src/cpu/operators/internal/CpuGemmAssemblyDispatch.h b/src/cpu/operators/internal/CpuGemmAssemblyDispatch.h new file mode 100644 index 0000000000..44c5c189a5 --- /dev/null +++ b/src/cpu/operators/internal/CpuGemmAssemblyDispatch.h @@ -0,0 +1,198 @@ +/* + * Copyright (c) 2018-2024 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ACL_SRC_CPU_OPERATORS_INTERNAL_CPUGEMMASSEMBLYDISPATCH_H +#define ACL_SRC_CPU_OPERATORS_INTERNAL_CPUGEMMASSEMBLYDISPATCH_H + +#include "arm_compute/function_info/ActivationLayerInfo.h" + +#include "src/core/common/Macros.h" +#include "src/cpu/ICpuOperator.h" + +namespace arm_compute +{ +namespace cpu +{ +/* Convolution method supported by the assembly gemm interface */ +enum class AsmConvMethod +{ + Im2Col, + Indirect, + Conv +}; + +struct AsmGemmInfo +{ + AsmConvMethod method{AsmConvMethod::Im2Col}; + PadStrideInfo ps_info{}; + ActivationLayerInfo activation_info{}; + GEMMLowpOutputStageInfo output_stage{}; + bool negated_offsets{true}; + bool reinterpret_input_as_3d{false}; + bool depth_output_gemm3d{false}; + int64_t padding_top{0}; + int64_t padding_left{0}; + float padding_value{0.f}; + bool fast_mode{false}; + bool fixed_format{false}; + arm_compute::WeightFormat weight_format{arm_compute::WeightFormat::UNSPECIFIED}; + bool reshape_b_only_on_first_run{true}; + bool accumulate{false}; + /** Whether we want to perform an additional transpose of b before passing it to gemm or pretranspose_B_array + * @note This transpose b operation is also considered a form of "reshape" or "transform", so should be counted for + * by the reshape_b_only_on_first_run flag + * @note This flag will be silently ignored (assumed to be false) when the weight_format is a fixed format. Because + * fixed format kernels do not accept weights (B) with any prior transformations + */ + bool transpose_b{false}; +}; + +/** Assembly kernel glue */ +class CpuGemmAssemblyDispatch : public ICpuOperator +{ +public: + /** Constructor */ + CpuGemmAssemblyDispatch(); + /** Defautl destructor */ + ~CpuGemmAssemblyDispatch() = default; + + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuGemmAssemblyDispatch); + + class IFallback + { + public: + virtual void run(ITensorPack &tensors) = 0; + virtual void prepare(ITensorPack &tensors) = 0; + virtual experimental::MemoryRequirements workspace() const = 0; + virtual bool is_configured() const = 0; + virtual bool isVarWeightsKernel() const = 0; + virtual ~IFallback() = default; + }; + +public: + /** If supported create a Compute Library function else fallback to the arm_gemm function. + * + * @note Configuring "batches" + * The shapes of @p a @p b and @p d are arranged as follows: + * Lowest dimension <-> Highest dimension + * a: [K, M, Batch, Multi] + * b: [N, K, Multi] + * d: [N, M, Batch, Multi] + * + * The "Batch" refers to where "Batch" number of MxK slices of tensor a multiplies with a single KxN slice of b + * The "Multi" refers to where "Multi" number of individual multiplication of a with b + * + * E.g. the following are some example input shape configurations + * + * (1) Normal 2D gemm + * a: [K=3, M=4] + * b: [N=5, K=3] + * d: [N=5, M=4] + * + * (2) Batches of a sharing b (e.g. gemm-based batched convolution where b is the shared ) + * a: [K=3, M=4, Batch=9] + * b: [N=5, K=3] + * d: [N=5, M=4, Batch=9] + * + * (3) "Batches" of independent gemm (e.g. batched matmul) + * a: [K=3, M=4, Batch=1, Multi=7] + * b: [N=5, K=3, Multi=7] + * d: [N=5, M=4, Batch=1, Multi=7] + * + * (4) "Batches" of independent gemm where b is also shared + * a: [K=3, M=4, Batch=4, Multi=7] + * b: [N=5, K=3, Multi=7] + * d: [N=5, M=4, Batch=4, Multi=7] + * + * @param[in] a Input tensor (Matrix A) + * @param[in] b Input tensor (Matrix B) + * @param[in] c Input tensor (Matrix C) used to pass the bias for quantized calculations + * @param[out] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] info GEMM meta-data + */ + void configure( + const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, ITensorInfo *d, const AsmGemmInfo &info); + + /** Indicates whether or not this function can be used to process the given parameters. + * + * @param[in] a Input tensor info (Matrix A) + * @param[in] b Input tensor info (Matrix B) + * @param[in] c Input tensor info (Matrix C) used to pass the bias for quantized calculations + * @param[in] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] info GEMM meta-data + * + * @return a status. + */ + static Status validate(const ITensorInfo *a, + const ITensorInfo *b, + const ITensorInfo *c, + const ITensorInfo *d, + const AsmGemmInfo &info); + + /** Indicates whether or not there is an optimal assembly implementation that can be used to process the given parameters. + * + * This method has the same use of @ref + * NEGEMMConvolutionLayer::has_opt_impl, with the only caveat that + * the value of arm_compute::WeightFormat need to be passed via the + * parameter info. + * + * @return a status. + */ + static Status has_opt_impl(arm_compute::WeightFormat &weight_format, + const ITensorInfo *a, + const ITensorInfo *b, + const ITensorInfo *c, + const ITensorInfo *d, + const AsmGemmInfo &info); + /** Checks if activation is supported by the gemm assembly dispatcher + * + * @param[in] activation Activation to check + * + * @return True if activation is supported else false + */ + static bool is_activation_supported(const ActivationLayerInfo &activation); + /** Was the function successfully configured ? + * + * @return True if the function is configured and ready to run + */ + bool is_configured() const; + /** Indicates if the convolution executes in variable weights mode. + * + * Similar to @ref CpuGemm::isVarWeightsKernel + */ + bool isVarWeightsKernel() const + { + return _arm_gemm && _arm_gemm->isVarWeightsKernel(); + } + + // Inherited methods overridden: + void prepare(ITensorPack &tensors) override; + void run(ITensorPack &tensors) override; + experimental::MemoryRequirements workspace() const override; + +private: + std::unique_ptr<IFallback> _arm_gemm; /**< Interface for the arm_gemm fallback */ +}; +} // namespace cpu +} // namespace arm_compute +#endif // ACL_SRC_CPU_OPERATORS_INTERNAL_CPUGEMMASSEMBLYDISPATCH_H |